
Dataset.   We use the UCI Adult datasethttps://archive.ics.uci.edu/ml/datasets/Adult, which comes divided into a training and a test set.
On the training set, we train Random Forest classifiers for both predicting the label (income: \(>50K\)  or not, using all features present in the dataset except gender) and the attribute (gender: “Male” or “Female” as categorized in the dataset, using all features except income).
We used the measure proposed in [1]} to evaluate
whether the independence assumption (REF ) (approximately) holds and found that
the independence assumption clearly fails to hold.
